---
license: apache-2.0
base_model: google/flan-t5-base
datasets:
- grammarly/coedit
tags:
- generated_from_trainer
- text-generation-inference
metrics:
- rouge
model-index:
- name: coedit-base
  results: []
language:
- en
widget:
- text: >-
    Fix the grammar: When I grow up, I start to understand what he said is quite
    right.
  example_title: Fluency
- text: >-
    Make this text coherent: Their flight is weak. They run quickly through the
    tree canopy.
  example_title: Coherence
- text: >-
    Rewrite to make this easier to understand: A storm surge is what forecasters
    consider a hurricane's most treacherous aspect.
  example_title: Simplification
- text: 'Paraphrase this: Do you know where I was born?'
  example_title: Paraphrase
- text: 'Write this more formally: omg i love that song im listening to it right now'
  example_title: Formalize
- text: 'Write in a more neutral way: The authors'' exposé on nutrition studies.'
  example_title: Neutralize
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# coedit-base

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the [CoEdIT dataset](https://huggingface.co/datasets/grammarly/coedit).

It achieves the following results on the evaluation set:
- Loss: 0.5978
- Rouge1: 60.5931
- Rouge2: 48.0165
- Rougel: 57.8997
- Rougelsum: 57.9335
- Gen Len: 16.6729

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 0.7478        | 1.0   | 6908  | 0.6452          | 59.7569 | 46.3099 | 56.4301 | 56.4464   | 16.6268 |
| 0.7127        | 2.0   | 13816 | 0.6086          | 60.2082 | 47.27   | 57.2356 | 57.2531   | 16.6513 |
| 0.7136        | 3.0   | 20724 | 0.6059          | 60.3747 | 47.6257 | 57.595  | 57.6184   | 16.6349 |
| 0.7038        | 4.0   | 27632 | 0.5999          | 60.5075 | 47.7856 | 57.7316 | 57.7698   | 16.6735 |
| 0.6911        | 5.0   | 34540 | 0.5978          | 60.5931 | 48.0165 | 57.8997 | 57.9335   | 16.6729 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.15.0